Navigation system interference locator

ABSTRACT

According to some embodiments of the present invention there is provided a method for detecting locations of navigation interfering devices. The method comprises an action of receiving multiple navigation signal parameter datasets, each from one of multiple satellite signal receivers. The method comprises an action of detecting one or more interference event data according to an interference analysis of at least some of the datasets. The method comprises an action of updating a probability value for each of multiple suspected navigation interference device locations, by a location analysis of the interference event data, where each of the probability values is indicative of a likelihood that the interference event data originates from some of the suspected navigation interference device locations. The method comprises an action of selecting a subset of the suspected navigation interference device locations according to the probability values and outputting the subset.

RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/043,634 filed on Feb. 15, 2016, which claims the benefit of priorityunder 35 USC 119(e) of U.S. Provisional Patent Application No.62/168,833 filed on May 31, 2015 and Israel Patent Application No.239103 filed on May 31, 2015.

The contents of the above applications are all incorporated by referenceas if fully set forth herein in their entirety

FIELD AND BACKGROUND OF THE INVENTION

The present invention, in some embodiments thereof, relates tonavigation systems and, more specifically, but not exclusively, tolocating devices interfering with navigation satellite signals.

A Satellite Navigation System (SNS) receiver determines its position byextracting its distance to navigation satellites. The satellitenavigation system may have coverage for worldwide (global), regional,national, and the like, geographic areas. For example, the NAVSTARGlobal Positioning System (GPS), the Russian GLObal NAvigation SatelliteSystem (GLONASS), the European Union's Galileo positioning system, andthe like, are Global Navigation Satellite System (GNSSs). For example,China's BeiDou Navigation Satellite System is a regional SNS.

Given the satellite's location and given the exact distance from eachsatellite to the SNS receiver, the SNS receiver's location may becomputed using triangulation functions. Since those distances arecomputed by Time-Of-Arrival (TOA) methods, inherent errors areinevitable, such as satellite signal delays caused by the atmosphere,and the like. Contemporary commercial SNS receivers may reach an errorbetween 2 to 5 meters in open sky locations, and in dense urban regions,the error may be as high as 50 meters or more.

Most commercial navigation applications handle such errors, whilemilitary and security SNS dependent systems need higher locationaccuracy. For some systems, knowing the location error is important,such as in risk awareness, evaluation of SNS dependent systems, such asmarine or air traffic control systems, and the like. Estimating the SNSreceiver's location error may be used for improving the SNS receiver'slocation accuracy.

Modern commercial SNS receivers are accurate in standard open regions,therefore uncertainty in the reported location may be caused bymalfunction, such as a broken antenna, external interference, and/or thelike. External SNS signal interference may be accidental interference,such as electromagnetic radiation noise, lack of satellite visibilitydue to obstructions, and/or the like, or deliberate interference, suchas SNS Jamming, Spoofing, and/or the like. Estimating the location errormay be relevant in both internal and external interferences.

SNS jammers are devices that generate electromagnetic radiation noise inthe carrier frequency of the SNS, such as 1.57 GHz for the L1 globalpositioning system (GPS), and the like. A SNS jammer transmitselectromagnetic radiation noise received by the SNS receiver, therebydegrading the Signal to Noise Ratio (SNR), such as when the SNS receiveris unable to report its location, referred to as loosing SNS fix.Jamming behavior is characterized by a sharp degradation of thesatellites signal SNR values. Different SNS jammers produce differentranges from several meters to several kilometers.

While jamming mainly causes signal noise at the SNS receiver, a moresophisticated jamming method exists for deliberate interference of SNSsignals, known as spoofing. SNS spoofers are transmitters that emitsignals identical to those sent by the SNS satellites to attempt tomislead the SNS receiver. During a spoofing attack, the SNS receiverloses its satellite lock on the genuine satellites.

SNS jamming interference is a major concern both in civilian andmilitary industries. SNS jamming affects not only SNS receivers, butalso SNS dependent systems, such as air traffic control systems, and thelike.

SUMMARY OF THE INVENTION

According to some embodiments of the present invention there is provideda method for detecting locations of navigation interfering devices. Themethod comprises an action of receiving multiple navigation signalparameter datasets, each from one of multiple satellite signalreceivers. The method comprises an action of detecting one or moreinterference event data according to an interference analysis of atleast some of the navigation signal parameter datasets. The methodcomprises an action of updating a probability value for each of multiplesuspected navigation interference device locations, by a locationanalysis of the interference event data, where each of the probabilityvalues is indicative of a likelihood that the interference event dataoriginates from some of the suspected navigation interference devicelocations. The method comprises an action of selecting a subset of thesuspected navigation interference device locations according to theprobability values and outputting the subset.

Optionally, the location analysis comprises a particle filter methoditeratively applied to the suspected navigation interference devicelocations, where each of the suspected navigation interference devicelocations is a particle and where in each iteration some of theprobability values are updated.

Optionally, each of the navigation signal parameter datasets is receivedby one of the satellite signal receivers from one of multiple navigationsignal transmitters.

Optionally, of the navigation signal transmitters is incorporated in anavigational satellite.

Optionally, each of the navigational signal transmitters belongs to aglobal navigation satellite system, a global positioning system, aregional navigation satellite system, and/or a local navigation system.

Optionally, the navigation signal parameter datasets are received byrespective satellite signal receivers at different times.

Optionally, the navigation signal parameter datasets are received byrespective satellite signal receivers at different locations.

Optionally, each of the interference event data corresponds to one ofthe satellite signal receivers.

Optionally, each interference event data comprises an event tag, anevent weight, an event location, and an event time.

Optionally, the suspected navigation interference device locationscomprise a location coordinates, a device transmission power value, adevice velocity value, and a device transmission orientation value.

Optionally, the selecting is performed by matching of the probabilityvalues to a threshold value and/or a distribution of values.

Optionally, the interference analysis is performed by calculating two ormore signal to noise ratio (SNR) values from some of the navigationsignal parameter datasets associated with one of the satellite signalreceivers.

Optionally, the location analysis is performed by calculating two ormore suspected distances from some of respective the satellite signalreceivers according to the SNR values, where each of the suspecteddistances defines an annular region of probability values aroundrespective one of the satellite signal receivers.

Optionally, the annular regions are combined to generate a probabilitymap of a geographical region.

Optionally, the subset is selected by calculating one or more peaks ofthe probability map.

Optionally, the device velocity value is calculated by analysis of atemporal change in the probability values.

Optionally, the interference analysis compares a value of a respectivenavigation signal parameter datasets with a known value.

Optionally, the compared value is a navigational signal transmitter timeof day and the known value is a satellite signal receiver time of day.

Optionally, the event weight is calculated from a reduction and/or anincrease in a signal to noise ratio (SNR) value derived from some of thenavigation signal parameter datasets.

Optionally, some of the navigation signal parameter datasets are fromone of the satellite signal receivers.

Optionally, the device transmission power is calculated from two or moreSNR values each derived from some of the navigation signal parameterdatasets.

Optionally, the SNR value is normalized by a peak SNR value computedfrom some of the navigation signal parameter datasets acquired over atime period.

Optionally, the peak SNR value is computed for one of the satellitesignal receivers.

Optionally, the peak SNR value is computed for one of two or morenavigational signal transmitters.

Optionally, the interference analysis is augmented by comparing a valueof some of the navigation signal parameter datasets with values from oneor more electromagnetic signals received by a cellular receiver, atelevision receiver, a Bluetooth receiver, and/or a wireless networkreceiver.

Optionally, the interference analysis is augmented by comparing a valueof some of the navigation signal parameter datasets with values from aposition sensor, a gyroscopic sensor, and/or an accelerometer.

According to some embodiments of the present invention there is provideda computer program product for detecting locations of navigationinterfering devices. The computer program product comprises a computerreadable storage medium having encoded thereon first programinstructions executable by a processor to cause the processor to receivetwo or more navigation signal parameter datasets each from one ofmultiple satellite signal receivers. The computer readable storagemedium has encoded thereon second program instructions executable by theprocessor to cause the processor to detect one or more interferenceevent data according to an interference analysis of at least some of thenavigation signal parameter datasets.

The computer readable storage medium has encoded thereon third programinstructions executable by the processor to cause the processor toupdate two or more probability values, each for one of multiplesuspected navigation interference device locations by a locationanalysis of the one or more interference event data. The probabilityvalues are each a likelihood of the interference event data originatingfrom respective one of the suspected navigation interference devicelocations. The computer readable storage medium has encoded thereonfourth program instructions executable by the processor to cause theprocessor to select a subset of the suspected navigation interferencedevice locations according to the probability values and output thesubset.

According to some embodiments of the present invention there is provideda computerized device for detecting locations of navigation interferingdevices. The computerized device comprises a satellite signal receivernetwork interface. The computerized device comprises a processor adaptedto receive two or more navigation signal parameter datasets each from asatellite signal receiver using the satellite signal receiver networkinterface. The processor is adapted to detect one or more interferenceevent data according to an interference analysis of at least some of thenavigation signal parameter datasets. The processor is adapted to updatea probability value for each of the suspected navigation interferencedevice locations by a location analysis of the interference event data,where the probability values are each a likelihood of the interferenceevent data originating from a respective one of the suspected navigationinterference device locations. The processor is adapted to select asubset of the suspected navigation interference device locationsaccording to the probability values and output the subset.

Unless otherwise defined, all technical and/or scientific terms usedherein have the same meaning as commonly understood by one of ordinaryskill in the art to which the invention pertains. Although methods andmaterials similar or equivalent to those described herein can be used inthe practice or testing of embodiments of the invention, exemplarymethods and/or materials are described below. In case of conflict, thepatent specification, including definitions, will control. In addition,the materials, methods, and examples are illustrative only and are notintended to be necessarily limiting.

Implementation of the method and/or system of embodiments of theinvention may involve performing or completing selected tasks manually,automatically, or a combination thereof. Moreover, according to actualinstrumentation and equipment of embodiments of the method and/or systemof the invention, several selected tasks could be implemented byhardware, by software or by firmware or by a combination thereof usingan operating system.

For example, hardware for performing selected tasks according toembodiments of the invention could be implemented as a chip or acircuit. As software, selected tasks according to embodiments of theinvention could be implemented as a plurality of software instructionsbeing executed by a computer using any suitable operating system. In anexemplary embodiment of the invention, one or more tasks according toexemplary embodiments of method and/or system as described herein areperformed by a data processor, such as a computing platform forexecuting a plurality of instructions. Optionally, the data processorincludes a volatile memory for storing instructions and/or data and/or anon-volatile storage, for example, a magnetic hard-disk and/or removablemedia, for storing instructions and/or data. Optionally, a networkconnection is provided as well. A display and/or a user input devicesuch as a keyboard or mouse are optionally provided as well.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The patent or application file contains at least one drawing executed incolor. Copies of this patent or patent application publication withcolor drawings will be provided by the Office upon request and paymentof the necessary fee.

Some embodiments of the invention are herein described, by way ofexample only, with reference to the accompanying drawings. With specificreference now to the drawings in detail, it is stressed that theparticulars shown are by way of example and for purposes of illustrativediscussion of embodiments of the invention. In this regard, thedescription taken with the drawings makes apparent to those skilled inthe art how embodiments of the invention may be practiced.

In the drawings:

FIG. 1 is a schematic illustration of a system for processing satellitesignals received by a SNS receiver to locate a jammer, according to someembodiments of the invention;

FIG. 2 is a flowchart for processing satellite signals received by SNSreceiver to locate a jammer, according to some embodiments of theinvention;

FIG. 3 is a graph of maximum signal to noise ratio versus distance to ajammer for several SNS receivers, according to some embodiments of theinvention;

FIG. 4A is a photograph illustrating a jammer location and SNS receiverrecording path, according to some embodiments of the invention;

FIG. 4B is a photograph illustrating a jammer location and SNS receiversignal strengths and reported locations, according to some embodimentsof the invention;

FIG. 4C is a photograph illustrating a jammer estimated location, andSNS receiver signal strengths from a single receiver at reportedlocations, overlaid with a jammer location probability map, according tosome embodiments of the invention; and

FIG. 4D is a photograph illustrating a jammer estimated location, andSNS receiver signal strengths from receivers at reported locations,overlaid with a jammer location probability map, according to someembodiments of the invention.

DETAILED DESCRIPTION

The present invention, in some embodiments thereof, relates tonavigation systems and, more specifically, but not exclusively, tolocating devices interfering with navigation satellite signals.

Single devices for satellite navigation system (SNS) jamminglocalization require expensive, dedicated SNS receiver hardware and aturnkey device, such as used by military satellite jamming detectors.Techniques for detecting SNS jammers using less expensive special SNSreceivers connected to multiple mobile devices has the advantage ofbeing more practical for civilian application, but the use of specialsatellite signal receivers requires a massive overhaul of existingmobile devices.

As used herein, the term navigation system means any navigation systembased on emitters of electromagnetic signals containing data of theemitters, such as position, time, and the like, and receiving devices(receivers), the record these signals and use the data from the signalsto determine the location of the receiving device. For example, termsGlobal Navigation Satellite Systems (GNSS), Global Positioning System(GPS), Satellite Navigation System (SNS) are satellite navigationsystems, and these terms may be used interchangeably herein to meannavigation systems.

Embodiments of the present invention may be applied to any navigationsystems that uses emitters for generating electromagnetic signals todetect and localize interference devices, such as jammers and the like,that interfere with these signals.

Using multiple SNS receivers for 3D mapping and real-time SNSpositioning improvement has been described by Irish et al in “Usingcrowdsourced satellite SNR measurements for 3D mapping and real-timeGNSS positioning improvement,” in Proceedings of the 6th annual workshopon Wireless of the students, by the students, for the students publishedby ACM, 2014, pp. 5-8, which is incorporated by reference in itsentirety. Jamming detection and localization using crowd sourcingmethods was also described by Scott in “J911: The case for fast jammerdetection and location using crowdsourcing approaches,” published inProceedings of the 24th International Technical Meeting of The SatelliteDivision of the Institute of Navigation, ION GNSS 2011, 2001, pp.1931-1940, incorporated in by reference in its entirety. Scott describesincorporating dedicated GPS Jam to Noise (J/N) ratio detectors in mobilephones to provide timely interference detection, such as is less than 10seconds, but the method requires new hardware not currently existing inmobile devices and a network infrastructure to collect information fromthe mobile devices to dedicated central computers.

According to some embodiments of the present invention, there areprovided systems and methods for receiving SNS datasets from one or moreSNS receivers, such as mobile device GPS receivers, and detecting alocation of SNS jammers from analysis of the datasets. When one or moreSNS receivers are affected by jamming interference from one or more SNSjamming devices, SNS raw datasets are sent from SNS receivers to acentral processor for analysis. Suspected SNS jammers' locations andtransmitting patterns are detected using a probability analysis of thesuspected jammer locations from the SNS datasets. A probability map ofSNS jammer locations may be used to cover all possible SNS jammerscenarios. As the SNS datasets are received, the suspected jammerlocation probability values and/or probability map is update until theSNS jammers are detected.

Optionally, a single SNS receiver receives multiple raw datasets fromthe SNS receivers. Using a single SNS receiver to localize a SNS jammermay use assumptions regarding the jammer's behavior, such as antennapattern, transmitting power, and the like. For example, when two or moreSNS jammers are interfering with the SNS satellite signals, extractingthe jammer locations from a single SNS receiver's datasets ischallenging.

Optionally, two or more SNS receivers send SNS raw datasets to a centralcomputer to locate one or more suspected SNS jammers. For example,analysis of datasets from multiple SNS receivers enables SNS jammingdetection and localization in complicated scenarios, such as moving SNSjammers, two or more SNS jammers, complex jamming patterns, and thelike. For example, analysis of SNS signal datasets from two or more SNSreceivers interfered with simultaneously is used to compute the SNSjammer's transmission power.

Optionally, the SNS raw data is used to extrapolate a SNS jammingcoverage map from a jamming interference probability map, allowing acontinuous prediction of each SNS receiver's error in a geographicregion.

Before explaining at least one embodiment of the invention in detail, itis to be understood that the invention is not necessarily limited in itsapplication to the details of construction and the arrangement of thecomponents and/or methods set forth in the following description and/orillustrated in the drawings and/or the Examples. The invention iscapable of other embodiments or of being practiced or carried out invarious ways.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers, and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages.

The computer readable program instructions may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures.

For example, two blocks shown in succession may, in fact, be executedsubstantially concurrently, or the blocks may sometimes be executed inthe reverse order, depending upon the functionality involved. It willalso be noted that each block of the block diagrams and/or flowchartillustration, and combinations of blocks in the block diagrams and/orflowchart illustration, can be implemented by special purposehardware-based systems that perform the specified functions or acts orcarry out combinations of special purpose hardware and computerinstructions.

Reference is now made to FIG. 1 and FIG. 2, which are a schematicillustration of a system and a flowchart, respectively, for processingsatellite signals received by a SNS receiver to locate a jammer,according to some embodiments of the invention. This example embodimentuses a GNSS as an example navigation system, but the example applies toall navigation systems using electromagnetic signals, such as GPS, SNS,and the like. A central computer 100 comprises a memory storing anInterference Event Module (IEM) 103 and a Jammer Localization Module(JLM) 104, each containing processor instructions for execution on oneor more processors 102. The central computer 100 comprises a receivernetwork interface 112 that connects the central computer 100 to anetwork 140 of GNSS receivers 120. For example, the network 140 is awireless network, a cellular network, an Ethernet network, and the like.

Initially, the JLM 104 comprises processor instructions to compute anumber of suspected jammer location possibilities 200 in a geographicalarea.

The IEM 103 comprises processor instructions to receive 201 GNSS signalparameter datasets from one or more GNSS receivers 121. Each datasetrepresents the signal parameters received by one GNSS receiver 121 froma GNSS signal 151 emitted by a GNSS satellite 150 at a certain time. TheIEM 103 comprises processor instructions to compare 202 the GNSSdatasets between receivers and at different times, to detect 203 one ofmore jamming event. When a jamming event is detected, data values arecomputed 203, by the central processor 102 according to the IEM 103instructions, relating to the jamming event, such as event weights,event time, estimated receiver location, and the like.

Following are details, according to some embodiments, of computingjamming event parameters by the central processor 102 using processorinstructions of the IEM 103. The IEM 103 comprises instructions tocompute signal to noise (SNR) values for each SNS receiver and eachsatellite. Each SNS receiver's maximal SNR value at a certain time t isdenoted SNR_(max)[t]. This value is per SNS receiver and/or mobiledevice GPS sensor, and represents the highest SNR value from all thevisible SNS satellites at a certain time t. The distance between the SNSreceiver and the SNS jammer at a time t is denote Jam_(dist)[t].

Reference is now made to FIG. 3, which is a graph of maximum signal tonoise ratio versus distance to a jammer for several SNS receivers,according to some embodiments of the invention. The curves 301, 302 and303 show the SNR values computed as a function of distance between theSNS receiver and the SNS jammer using a free space electromagneticpropagation 301, datasets from a smartphone GPS receiver 302, anddatasets from a dedicated SNS receiver with an external antenna 303,respectively. The curves show a positive, nonlinear correlation existsbetween SNR_(max) value and Jam_(dist), such that the SNR_(max) valuedecreases as the SNS receiver approaches the SNS jammer.

Optionally, each dataset and/or SNR value is calibrated by normalizingthe SNR values under jamming influence to optimal SNR_(max) values thatare typically higher than values received under interference and/orjamming. To normalize the SNR values, for each SNS receiver an optimalSNR value, denoted OPT_(SNR), is computed that is the maximal SNR valuethat receiver has received over a time, such as the maximum from alldatasets of one or more SNS receivers. Optionally, the optimal SNRvalues are computed for each SNS satellite from the correspondingdatasets, and used to normalize the SNR values from that satellite. Forexample, when each SNS satellite broadcasts SNS signals at differentpowers. For example, typical OPT_(SNR) values range between 41 to 45dB/Hz. Optionally, OPT_(SNR) is computed for each SNS receiverseparately from the other SNS receivers. For example, each SNS receiverhas a different receiver sensitivity and/or gain, and OPT_(SNR) iscomputed for each SNS receiver separately.

SNS jamming behavior may be detected by the processor(s) 102 bycomputing SNR_(max) values for different times and locations. As eachSNS receiver approaches a jammer, the SNR_(max) decreases and viseversa. A jamming event, denoted Jam_(event)[t], is an event in timeand/or location where jamming interference is suspected, such as bycomputing a probability value, a likelihood value, and the like. EachJam_(event)[t] may comprise event parameter values computed by processorinstructions of the IEM 103, such as the SNS receiver's location,denoted P, a weight value that indicates the strength of the jammingevent, and the like. Optionally, to eliminate duplicate events, such asin the case of stationary receivers, events are filtered by theprocessor(s) 102 using SNR_(max)[t]<SNR_(max)[t−1], such as when thereceiver moves towards a jammer. Optionally, the processor(s) 102filters jamming events to cases where the receiver moves away from thejammer, denoted Jam′_(event)[t], such as whenSNR_(max)[t]>SNR_(max)[t−1]. Optionally, both types of SNS receivermotion are filtered.

Weighted event values, denoted Jam_(weight)[t], may allow embodiments toapproximate the distance to each SNS jammer, denoted Jam_(dist),associated with the event. The weight may be evaluated asJam_(weight)[t]=(OPT_(SNR)−SNR_(max)[t])/OPT_(SNR). For example, whenthe event weight increases, Jam_(dist) decreases.

Given a known or estimated value for jammer transmission power, denotedJAM_(TX), the Jam_(dist)[t] may be computed for each event and aprobability associated with the suspected SNS jammer locations on anannular jammer location probability region surrounding the SNS receiverlocation, such as an annular region of probabilities according to valueof Jam_(dist)[t]. The value of Jam_(dist) may be a function ofJam_(weight). For example, the bigger the value of Jam_(weight), thesmaller the value of Jam_(dist). We denote Err as the annular region'sthickness where typical Err values are between 2 to 5 meters, such asthe thickness of an annular region of probabilities around the SNSreceiver location.

Optionally, the SNR values for each satellite are computed according tothe orientation between the receiver and each satellite to determine apreferential direction for a suspected jammer location probability. Forexample, the annular region of probabilities lies on a distorted annularregion.

Optionally, each Jam_(event) determines a set of Jam_(dist) valuesdefining probabilities at different distances from the reported receiverlocation.

Optionally, the SNS receiver time is compared to the satellite timeembedded in each dataset to compute a jamming event.

Optionally, when the SNS jammer's transmitting power, denoted JAM_(TX),is known and/or guessed, the location of one or more SNS jammers isdetected. Using an electromagnetic free space propagation model andgiven a known constant jamming transmission power, Jam_(dist) may becalculated. For example, the scale of the x-axis in FIG. 3 scales withJAM_(TX).

In embodiments of the present invention, a free space electromagneticpropagation model may be used to compute Jam_(dist), but other modelsmay be used, such as empirical models, statistical models, and the like.

Scaling Jam_(dist) according to the jamming events, such as byestimating JAM_(TX), may be performed by the processor(s) 102 byinspecting a receiver's two or more Jam_(event) parameters. For example,Jam_(dist) is computed using the geographic distance between jammingevents and the difference in SNR_(max) values. Utilizing regressiontechniques, an upper bound of JAM_(TX) may be computed by theprocessor(s) 102 from one or more receiver's Jam_(event) parameters.Even a coarse estimation of the JAM_(TX) may be sufficient forapproximating the jammer's position and region.

When datasets from SNS receivers are analyzed, a minimal bounding circlearound the SNS jammer location, denoted P, may be computed from jammingevent weights. The datasets may be from the same time, from similartimes, and/or from different times. The bounding circle's radius may beused to compute a JAM_(TX) estimation since JAM_(TX) is correlated withJam_(dist).

Following are details, according to some embodiments, of computingsuspected jammer location probabilities and parameters by theprocessor(s) 102 according to processor instructions of the JLM 104.

The JLM 104 comprises processor instructions to update 205 eachsuspected jammer location with a probability value based on each jammerevent, and optionally update 206 other suspected jammer parameters, suchas velocity, jamming pattern, jamming broadcasting orientation, and thelike. For example, the velocities of the jammers are computed based ontime series analysis of the jamming events parameter values. Accordingto the instructions of the JLM 104, jammers are detected 207 when theprobabilities match a rule and/or pattern, such as when one or moresuspected jammer location probabilities are above a probabilitythreshold, matching suspected jammer location probabilities to adistribution of probabilities, and/or the like. For example, theprobabilities of suspected jammers are plotted on a probability map, anda peak analysis of the probability map is performed to detect thejammers. In this example, when the peak is sufficiently narrow a SNSjammer is detected.

For each Jam_(event) an annular region of jammer location probabilitiesmay be embedded on a probability map, such as a two dimensional array ofprobability values, at a distant of Jam_(dist) around the SNS receiver'sreported location. By combining annular regions from multiple SNSjamming events, such as multiplication of the probability values at eachlocation, the probability map may show the location of a SNS jammer.

For multiple jamming events the one or more SNS jammers locations aredetected from the multiplying the annular regions of probability valuesof each jamming event. For example, the peak of a cluster of probabilityvalues computed from the annular region probability value smultiplications in the probability map. When the geographical region islarge, the distance between multiple jammers is large, and there aresufficient jamming events, multiple jammers may be detected as thepoints that intersect the majority of the annular regions. This exampleembodiment may require long convergence times, such as waiting for asufficient number of jamming events to achieve a required probabilityand/or a required level of confidence. An assumption of a known JAM_(TX)value may not be correct and the convergence may require some time. Forexample, when the SNS jammer is varying transmission power levels toavoid detection, the JAM_(TX) value computed from a datasets received bya single SNS receiver may not be correct.

Optionally, when multiple SNS jammers produce interference, the JLM 104comprises processor instructions to use probabilistic methods foranalysis of signal datasets. For example, received datasets are analyzedby the processor(s) 102 using a Monte Carlo method, a Bayesian method, aparticle filter method, a maximum likelihood method, a k-top survivalmethod, and/or the like.

According to some embodiments of the present invention, a particlefilter method may be used by the processor(s) 102 to update suspectedjammer location probabilities. As used herein, the term particle means asuspected jammer location and associated parameters. Similar tohistogram filters, particle filters estimate the posterior distributionof a finite number of parameters based on resampled measurements.Following is a mathematical analogy representing a particle filtermethod defined by the processor instruction in the JJM 104.

In the mathematical analogy, the samples of the posterior distributionare termed particles and represented as χt:=x_(t) ^([1]), x_(t) ^([2]),. . . , x_(t) ^([M]) where M is the number of particles. Each particle,such as a suspected jammer location, is represented by a belieffunction, denoted bel(x_(t)). For example, the greater the value ofbel(x) at a certain location, the greater the probability for a jammerto be located there. This belief function serves as the weight and/orimportance of each particle. Thus, the equation {(w_(t) ^((L)),x_(t)^((L))):L∈{1, . . . , M}} represents a weight w_(t) for each particlex_(t). The weight and/or importance value is proportional to thelikelihood of a specific particle being an SNS jammer: x_(t)^([L])˜p(x_(t)|z_(1:t),u_(1:t))×w_(t) ^((L)) where z_(1:t) and u_(1:t)are sense and action functions, respectively.

For example, action functions are estimates of each jammer's velocityvector, such as a magnitude and heading. The Bayesian theorem impliesthat the estimation in t₁ is derived from the estimation in Ft₀. Theremay be more than a single plausible solution when using probabilisticmethods. For example, multiple SNS jammers, each represented as aparticle in the above mathematical analogy, are detected simultaneously.As used herein, the term particle means a particular SNS jammer with anassociated suspected jammer location probability and parameters.

The particle parameters, such as SNS jammer parameters, are repeatedlyupdated by the processor(s) 102 with each jamming event according totheir respective weight and/or probability. For example, particles withhigh weights and/or probabilities are more likely to survive eachiteration.

A particle x(t)^([L]) is a candidate location for a jammer device attime t. Each particle comprises parameters such as a position, velocity,orientation and transmitting power, such as JAM_(TX)(L,t), and the like.For example, stationary jammers have a velocity equal to zero.

A particle filter method may address the complicated jamming scenario ofmoving jammers and dynamic transmitting power. Moving SNS jammers affectthe different SNS receivers in the region in different ways. Forexample, when a jammer moves from location A to location B, SNSreceivers next to be B may report Jam_(event) with decreasing SNR whilereceivers next to A report the opposite.

Changes in the transmitting power of the SNS jammer may affect all thereceivers the same way, such as when a jammer is turned off SNR_(max)may increase or stay the same for all the SNS receivers concurrently.Suspected locations of SNS jammers are spread over the geographicalregion, and each jammer comprises a location, velocity, and/or the like.Then, the action function, u_(t) is executed. Each action function maymove a particle, such as according to its velocity, and/or change itstransmitting power, thus, changing its interference region's radius.

The sense function, z_(t), produces a weight and/or likelihood for eachparticle based on the receiver's GNSS data. The resampling stage favorsthe more likely particles, such as particles with a higher probabilityvalue. Assuming a 10 Hz dataset sampling rate and N number of particlesthat is greater than the number of SNS jammers, the method executed bythe processor(s) 102 converges to detect clusters of particles. Forexample, two or more clusters imply two or more SNS jammers activesimultaneously within the geographical region.

When the SNS jammers are detected with sufficient probability by theprocessor(s) 102, the JLM 104 comprises instructions to output 208parameters of the detected jammer(s), such as to a user interface 111.

Following are results of computing jamming events and suspected jammerlocation probabilities, according to some embodiments of the presentinvention.

Reference is now made to FIG. 4A, which is a photograph illustrating ajammer location and SNS receiver recording path, according to someembodiments of the invention. A portable GPS jammer with 40 metersjamming range was placed on a tree, represented as a black star 401.Several GPS receivers 121 we moved along the yellow path 402 whilerecording GNSS datasets. The GNSS datasets were received by a centralcomputer 100 and analyzed by the processor(s) 102.

Reference is now made to FIG. 4B, which is a photograph illustrating ajammer location and SNS receiver signal strengths and reportedlocations, according to some embodiments of the invention. The coloreddots 404 represent the GNSS dataset values along the recorded path 402.Each color represents values of SNR_(max)[t] 405. Green dots representSNR_(max)[t]≥40, blue dots represent 34≤SNR_(max)[t]<40, and the like.The colored dots 404 show that SNR_(max)[t] degrades 406 as the receiverapproaches the jammer 401 and vice versa. Along the path the SNSreceiver did not record loosing fix events, but some satellites becameinvisible, a phenomena that affects the GPS location accuracy. Thedifference between the original yellow path 402 and the recorded GNSSpath 404 represent the location error due to the SNS jammerinterference.

Reference is now made to FIG. 4C, which is a photograph illustrating ajammer estimated location, and SNS receiver signal strengths from asingle receiver at reported locations, overlaid with a jammer locationprobability map, according to some embodiments of the invention. Eachjamming probability annular region 411 assigns suspected jammer locationprobabilities on to the probability map. Multiplying the probabilityannular regions from each jamming event allows detection of a peakprobability at a suspected jammer's location represented by the redregion 410. The error in suspected jammer's location is about 5 meters.

Reference is now made to FIG. 4D, which is a photograph illustrating ajammer estimated location, and SNS receiver signal strengths fromreceivers at reported locations, overlaid with a jammer locationprobability map, according to some embodiments of the invention. ThreeSNS receivers recorded SNR_(max) values along the path 402 of FIG. 4A,where the colored dots 422 represent ranges of SNR_(max) values as inFIG. 4B. Combining the annular regions of probability values forsuspected jammer locations produces a probability map 421, where thebrighter gray levels are the greater probability and/or likelihood for ajammer at that location in the region. The brightest region 420, markedin red, is the highest probability of the jammer's location, and may beused as an estimate for the SNS jammer's location. The error in jammerlocation is less than 2 meters.

The improvement in error of estimating the SNS jammer's location usingthree SNS receivers instead of one is illustrated as the larger size ofthe red region 410 in FIG. 4C compared to the red region 420 of FIG. 4D.This may be due to the noise of each receiver, which is compensated forwhen datasets form multiple receivers are analyzed. Further, the SNSreceiver estimated location error in the FIG. 4C is larger, as seen byboth blue and green dots inside the red region 410 on FIG. 4C.

Optionally, an embedded microcontroller may be the central processor.For example, a 32-bit microcontroller unit, such as an ARM Cortex M4processor, is the central processor. For example, one of the SNSreceivers comprises a central processor. For example, the SNS receiverwith a processor is smaller than a pack of cigarettes, a book ofmatches, and the like. For example, the central processor is a processorof a smartphone, tablet, mobile device, and the like. For example, theSNS receiver records datasets at a 10 Hz sampling rate, and the centralprocess detects SNS jammers at a 1 Hz sampling rate.

The methods as described above may be used in the fabrication ofintegrated circuit chips.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof code, which comprises one or more executable instructions forimplementing the specified logical function(s). It should also be notedthat, in some alternative implementations, the functions noted in theblock may occur out of the order noted in the figures. For example, twoblocks shown in succession may, in fact, be executed substantiallyconcurrently, or the blocks may sometimes be executed in the reverseorder, depending upon the functionality involved. It will also be notedthat each block of the block diagrams and/or flowchart illustration, andcombinations of blocks in the block diagrams and/or flowchartillustration, can be implemented by special purpose hardware-basedsystems that perform the specified functions or acts, or combinations ofspecial purpose hardware and computer instructions.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

It is expected that during the life of a patent maturing from thisapplication many relevant navigation systems will be developed and thescope of the term satellite navigation system (SNS) is intended toinclude all such new technologies a priori.

It is expected that during the life of a patent maturing from thisapplication many relevant global positioning systems will be developedand the scope of the term global positioning systems is intended toinclude all such new technologies a priori.

It is expected that during the life of a patent maturing from thisapplication many relevant SNS jammers will be developed and the scope ofthe term SNS jammers is intended to include all such new technologies apriori.

It is expected that during the life of a patent maturing from thisapplication many relevant SNS receivers will be developed and the scopeof the term SNS receivers is intended to include all such newtechnologies a priori.

As used herein the term “about” refers to ±10%.

The terms “comprises”, “comprising”, “includes”, “including”, “having”and their conjugates mean “including but not limited to”. This termencompasses the terms “consisting of” and “consisting essentially of”.

The phrase “consisting essentially of” means that the composition ormethod may include additional ingredients and/or steps, but only if theadditional ingredients and/or steps do not materially alter the basicand novel characteristics of the claimed composition or method.

As used herein, the singular form “a”, “an” and “the” include pluralreferences unless the context clearly dictates otherwise. For example,the term “a compound” or “at least one compound” may include a pluralityof compounds, including mixtures thereof.

The word “exemplary” is used herein to mean “serving as an example,instance or illustration”. Any embodiment described as “exemplary” isnot necessarily to be construed as preferred or advantageous over otherembodiments and/or to exclude the incorporation of features from otherembodiments.

The word “optionally” is used herein to mean “is provided in someembodiments and not provided in other embodiments”. Any particularembodiment of the invention may include a plurality of “optional”features unless such features conflict.

Throughout this application, various embodiments of this invention maybe presented in a range format. It should be understood that thedescription in range format is merely for convenience and brevity andshould not be construed as an inflexible limitation on the scope of theinvention. Accordingly, the description of a range should be consideredto have specifically disclosed all the possible subranges as well asindividual numerical values within that range. For example, descriptionof a range such as from 1 to 6 should be considered to have specificallydisclosed subranges such as from 1 to 3, from 1 to 4, from 1 to 5, from2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numberswithin that range, for example, 1, 2, 3, 4, 5, and 6. This appliesregardless of the breadth of the range.

Whenever a numerical range is indicated herein, it is meant to includeany cited numeral (fractional or integral) within the indicated range.The phrases “ranging/ranges between” a first indicate number and asecond indicate number and “ranging/ranges from” a first indicate number“to” a second indicate number are used herein interchangeably and aremeant to include the first and second indicated numbers and all thefractional and integral numerals therebetween.

It is appreciated that certain features of the invention, which are, forclarity, described in the context of separate embodiments, may also beprovided in combination in a single embodiment. Conversely, variousfeatures of the invention, which are, for brevity, described in thecontext of a single embodiment, may also be provided separately or inany suitable subcombination or as suitable in any other describedembodiment of the invention. Certain features described in the contextof various embodiments are not to be considered essential features ofthose embodiments, unless the embodiment is inoperative without thoseelements.

Although the invention has been described in conjunction with specificembodiments thereof, it is evident that many alternatives, modificationsand variations will be apparent to those skilled in the art.Accordingly, it is intended to embrace all such alternatives,modifications and variations that fall within the spirit and broad scopeof the appended claims.

All publications, patents and patent applications mentioned in thisspecification are herein incorporated in their entirety by referenceinto the specification, to the same extent as if each individualpublication, patent or patent application was specifically andindividually indicated to be incorporated herein by reference. Inaddition, citation or identification of any reference in thisapplication shall not be construed as an admission that such referenceis available as prior art to the present invention. To the extent thatsection headings are used, they should not be construed as necessarilylimiting.

What is claimed is:
 1. A method for detecting locations of navigationinterfering devices comprising: detecting at least one interferenceevent data according to an interference analysis of a plurality ofnavigation signal parameter datasets received from a plurality ofsatellite signal receivers; mapping calculating a plurality of suspectednavigation interference device locations by a location analysis of saidat least one interference event data; and plotting at least some of theplurality of suspected navigation interference device locations on a mapof a geographical region; and outputting said map.
 2. The method ofclaim 1, wherein said mapping further comprising updating a plurality ofprobability values each for one of said plurality of suspectednavigation interference device locations, wherein each one of saidplurality of probability values is indicative of a likelihood that saidat least one interference event data originates from some of saidplurality of suspected navigation interference device locations.
 3. Themethod of claim 2, wherein said plotting is performed according to theplurality of probability values.
 4. The method of claim 2, wherein saidlocation analysis comprises a particle filter method iteratively appliedto said plurality of suspected navigation interference device locations,wherein each of said plurality of suspected navigation interferencedevice locations is considered one of a plurality of particles andwherein in each iteration some of said plurality of probability valuesare updated.
 5. The method of claim 1, wherein each of said plurality ofnavigation signal parameter datasets is received by one of saidplurality of satellite signal receivers from one of a plurality ofnavigation signal transmitters.
 6. The method of claim 5, wherein eachof said plurality of navigation signal transmitters are incorporated inone of a plurality of navigational satellites.
 7. The method of claim 5,wherein each of said plurality of navigational signal transmittersbelongs to one of a global navigation satellite system, a globalpositioning system, a regional navigation satellite system, and a localnavigation system.
 8. The method of claim 1, wherein said plurality ofnavigation signal parameter datasets are received by respective saidplurality of satellite signal receivers at different times.
 9. Themethod of claim 1, wherein said plurality of navigation signal parameterdatasets are received by respective said plurality of satellite signalreceivers at different locations.
 10. The method of claim 1, whereineach of said at least one interference event data corresponds to one ofsaid plurality of satellite signal receivers.
 11. The method of claim 1,wherein said at least one interference event data comprises an eventtag, an event weight, an event location, and an event time.
 12. Themethod of claim 1, wherein said plurality of suspected navigationinterference device locations comprise a location coordinates, a devicetransmission power value, a device velocity value, and a devicetransmission orientation value.
 13. The method of claim 1, wherein saidinterference analysis is performed by calculating a plurality of signalto noise ratio (SNR) values from some of said plurality of navigationsignal parameter datasets associated with one of said plurality ofsatellite signal receivers.
 14. The method of claim 13, wherein saidlocation analysis is performed by calculating a plurality of suspecteddistances from some of respective said plurality of satellite signalreceivers, wherein each of said plurality of suspected distances definesan annular region of probability values around respective one of saidplurality of satellite signal receivers.
 15. The method of claim 14,wherein said map is a probability map and said annular regions arecombined to generate a probability map of a geographical region.
 16. Themethod of claim 15, wherein said at least some of the plurality ofsuspected navigation interference device locations are selected bycalculating at least one peak of said probability map.
 17. The method ofclaim 1, wherein said interference analysis compares a value ofrespective some of said navigation signal parameter datasets with arespective known value.
 18. The method of claim 1, wherein saidinterference analysis is augmented by comparing a value of some of saidnavigation signal parameter datasets with values from at least oneelectromagnetic signal received by at least one of a cellular receiver,a television receiver, a Bluetooth receiver, and a wireless networkreceiver.
 19. A computer program product for detecting locations ofnavigation interfering devices, said computer program productcomprising: a computer readable storage medium having encoded thereon:first program instructions executable by a processor to cause saidprocessor to detect at least one interference event data according to aninterference analysis of a plurality of navigation signal parameterdatasets received from a plurality of satellite signal receivers; secondprogram instructions executable by said processor to cause saidprocessor to map calculating a plurality of suspected navigationinterference device locations by a location analysis of said at leastone interference event data; and third program instructions executableby said processor to cause said processor to plot at least some of theplurality of suspected navigation interference device locations on a mapof a geographical region; and fourth program instructions executable bysaid processor to cause said processor to output said map.
 20. Acomputerized device for detecting locations of navigation interferingdevices, comprising: a satellite signal receiver network interface; anda processor adapted to: detect at least one interference event dataaccording to an interference analysis of a plurality of navigationsignal parameter datasets received from a plurality of satellite signalreceivers; map calculating a plurality of suspected navigationinterference device locations by a location analysis of said at leastone interference event data; and plot at least some of the plurality ofsuspected navigation interference device locations on a map of ageographical region; and output said map.